Coordinate Descent Method
Distributed Coordinate Descent Method for Learning with Big Data
... dual coordinate ascent method (parallelizing the original SDCA methods of Hsieh et ...subgradient descent method (Pegasos of Shalev- Shwartz et ...parallel coordinate descent ...
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Coordinate Descent Method for Large-scale L2-loss Linear Support Vector Machines
... proposed coordinate descent method to solve logistic regression, which is twice ...using coordinate decent methods for logistic regression/maximum entropy is by Miroslav et ...our ...
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A distributed block coordinate descent method for training l1 regularized linear classifiers
... Generic Coordinate Descent Method (Scherrer et ...for coordinate descent methods ( GenCD ) suitable for parallel computing ...Several coordinate de- scent algorithms such as ...
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Antenna Array Pattern Synthesis via Coordinate Descent Method
... In this article, an array pattern synthesis algorithm for arbitrary arrays based on coordinate descent method (CDM) is presented. CDM has been first mentioned in [26] for solving smooth unconstrained ...
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Weighted Oblique Decision Trees
... the coordinate descent ...square method and linear discrim- inant analysis (Brodley and Utgoff 1995; Loh and Shih 1997; Bennett and Blue 2002; L´opez-Chau et ...
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QUIC: Quadratic Approximation for Sparse Inverse Covariance Estimation
... order method to (2) after smoothing the objective function; Scheinberg et ...Lagrangian method to handle the smooth and nonsmooth parts separately; the resulting algorithm is implemented in the ALM software ...
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Iterative Scaling and Coordinate Descent Methods for Maximum Entropy Models
... Maximum entropy (Maxent) is useful in natural language processing and many other areas. Iterative scaling ( IS ) methods are one of the most popular approaches to solve Maxent. With many variants of IS methods, it is ...
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PubMedCentral-PMC5120762.pdf
... constraints. Therefore, the dual optimization (8) and can be solved by the well known coordinate descent method. Furthermore, because the object function is quadratic, within each step of ...
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Asynchronous Delay-Aware Accelerated Proximal Coordinate Descent for Nonconvex Nonsmooth Problems
... stochastic coordinate descent prox-SCD (Shalev-Shwartz and Tewari 2011), prox- SVRG (Xiao and Zhang 2014), prox-SAGA (Defazio, Bach, and Lacoste-Julien 2014), prox-SDCA (Shalev-Shwartz and Zhang ...
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Linear Convergence of Randomized Feasible Descent Methods Under the Weak Strong Convexity Assumption
... feasible descent method FDM to a randomized, and a randomized coordinate, FDM ...cyclic coordinate descent method, the coefficients in FDM are worse than, or similar to, the ...
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A Comparison of Optimization Methods and Software for Large-scale L1-regularized Linear Classification
... cyclic coordinate descent ...considered coordinate descent methods, although they allowed a block of variables at each ...a coordinate descent method, but used the ...
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On Faster Convergence of Cyclic Block Coordinate Descent-type Methods for Strongly Convex Minimization
... block coordinate descent-type (CBCD-type) methods, which perform iterative updates for a few coordinates (a block) simultaneously throughout the procedure, have shown remarkable computational performance ...
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Group lassoing change-points in piecewise-constant AR processes
... using block-coordinate descent iterations. The latter incurs computational burden that scales linearly with the number of data samples, thus being particularly attractive for large-size problems. ...
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An efficient algorithm for steepest descent method for unconstrained optimization
... Barzilai-Borwein method ensures superlinear convergence and performs quite ...Barzilai-Borwein method is not monotone, thus it is not easy to be generalized for general nonlinear ...
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Accelerating Cross-Validation in Multinomial Logistic Regression with $\ell_1$-Regularization
... A sensitive point which should be noted is the convergence problem of the algorithm for solving the present optimization problem. In Glmnet, a specialized version of coordinate descent methods is employed, ...
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The Effect of Adaptive Gain and Adaptive Momentum in Improving Training Time of Gradient Descent Back Propagation Algorithm on Classification Problems
... In recent years, a number of research studies have attempted to overcome these problems. These involved the development of heuristic techniques, based on studies of properties of the conventional back propagation ...
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Analysis of Optimization Methods in Multisteerable Filter Design
... The research presented in the thesis provides a practical method for estimating the orientation of corners in real images. The journal paper by Muhlich, Friedrich, and Aach presented the theory of efficiently ...
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A generalized descent method for global optimization
... For a minimizer of a convex minimization problem with a differentiable objective function we have the condition that the inner product between the local gradient and any direction contai[r] ...
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Two criteria in Fermat infinite descent method
... A comparison of Eqs. (II.3) and (II.7) shows that the power of 2 in is less than the power of 2 in u by one. After a finite number of steps of the descent the corresponding even parameter u becomes odd. Then all ...
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A projection descent method for solving variational inequalities
... Remark (a) The proposed method can be viewed as a refinement and improvement of the method of He et al. [] by performing an additional projection step at each itera- tion and another optimal step length ...
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